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• How to Write a Research Proposal | Examples & Templates

How to Write a Research Proposal | Examples & Templates

Published on 30 October 2022 by Shona McCombes and Tegan George. Revised on 13 June 2023.

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research.

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Introduction

Literature review.

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organised and feel confident in the path forward you choose to take.

Table of contents

Research proposal purpose, research proposal examples, research design and methods, contribution to knowledge, research schedule, frequently asked questions.

Academics often have to write research proposals to get funding for their projects. As a student, you might have to write a research proposal as part of a grad school application , or prior to starting your thesis or dissertation .

In addition to helping you figure out what your research can look like, a proposal can also serve to demonstrate why your project is worth pursuing to a funder, educational institution, or supervisor.

Research proposal length

The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.

One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.

Download our research proposal template

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Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.

• Example research proposal #1: ‘A Conceptual Framework for Scheduling Constraint Management’
• Example research proposal #2: ‘ Medical Students as Mediators of Change in Tobacco Use’

Like your dissertation or thesis, the proposal will usually have a title page that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.

Your introduction should:

• Introduce your topic
• Give necessary background and context
• Outline your  problem statement  and research questions

To guide your introduction , include information about:

• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights your research will contribute
• Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or synthesise prior scholarship

Following the literature review, restate your main  objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasise again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .

Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.

Here’s an example schedule to help you get started. You can also download a template at the button below.

Download our research schedule template

If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.

Make sure to check what type of costs the funding body will agree to cover. For each item, include:

• Cost : exactly how much money do you need?
• Justification : why is this cost necessary to complete the research?
• Source : how did you calculate the amount?

To determine your budget, think about:

• Travel costs : do you need to go somewhere to collect your data? How will you get there, and how much time will you need? What will you do there (e.g., interviews, archival research)?
• Materials : do you need access to any tools or technologies?
• Help : do you need to hire any research assistants for the project? What will they do, and how much will you pay them?

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement.

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.

A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.

A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.

All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

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Writing a Rsearch Proposal

A  research proposal  describes what you will investigate, why it’s important, and how you will conduct your research.  Your paper should include the topic, research question and hypothesis, methods, predictions, and results (if not actual, then projected).

Research Proposal Aims

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

• Introduction

Literature review

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Proposal Format

The proposal will usually have a  title page  that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

Introduction The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.. Your introduction should:

• Introduce your  topic
• Give necessary background and context
• Outline your  problem statement  and  research questions To guide your  introduction , include information about:  
• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights will your research contribute
• Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong  literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or  synthesize  prior scholarship

Research design and methods

Following the literature review, restate your main  objectives . This brings the focus back to your project. Next, your  research design  or  methodology  section will describe your overall approach, and the practical steps you will take to answer your research questions. Write up your projected, if not actual, results.

Contribution to knowledge

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Lastly, your research proposal must include correct  citations  for every source you have used, compiled in a  reference list . To create citations quickly and easily, you can use free APA citation generators like BibGuru. Databases have a citation button you can click on to see your citation. Sometimes you have to re-format it as the citations may have mistakes. 

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How To Write A Research Proposal

A Straightforward How-To Guide (With Examples)

By: Derek Jansen (MBA) | Reviewed By: Dr. Eunice Rautenbach | August 2019 (Updated April 2023)

Writing up a strong research proposal for a dissertation or thesis is much like a marriage proposal. It’s a task that calls on you to win somebody over and persuade them that what you’re planning is a great idea. An idea they’re happy to say ‘yes’ to. This means that your dissertation proposal needs to be   persuasive ,   attractive   and well-planned. In this post, I’ll show you how to write a winning dissertation proposal, from scratch.

Before you start:

– Understand exactly what a research proposal is – Ask yourself these 4 questions

The 5 essential ingredients:

• The title/topic
• The introduction chapter
• The scope/delimitations
• Preliminary literature review
• Design/ methodology
• Practical considerations and risks 

What Is A Research Proposal?

The research proposal is literally that: a written document that communicates what you propose to research, in a concise format. It’s where you put all that stuff that’s spinning around in your head down on to paper, in a logical, convincing fashion.

Convincing   is the keyword here, as your research proposal needs to convince the assessor that your research is   clearly articulated   (i.e., a clear research question) ,   worth doing   (i.e., is unique and valuable enough to justify the effort), and   doable   within the restrictions you’ll face (time limits, budget, skill limits, etc.). If your proposal does not address these three criteria, your research won’t be approved, no matter how “exciting” the research idea might be.

PS – if you’re completely new to proposal writing, we’ve got a detailed walkthrough video covering two successful research proposals here . 

How do I know I’m ready?

Before starting the writing process, you need to   ask yourself 4 important questions .  If you can’t answer them succinctly and confidently, you’re not ready – you need to go back and think more deeply about your dissertation topic .

You should be able to answer the following 4 questions before starting your dissertation or thesis research proposal:

• WHAT is my main research question? (the topic)
• WHO cares and why is this important? (the justification)
• WHAT data would I need to answer this question, and how will I analyse it? (the research design)
• HOW will I manage the completion of this research, within the given timelines? (project and risk management)

If you can’t answer these questions clearly and concisely,   you’re not yet ready   to write your research proposal – revisit our   post on choosing a topic .

If you can, that’s great – it’s time to start writing up your dissertation proposal. Next, I’ll discuss what needs to go into your research proposal, and how to structure it all into an intuitive, convincing document with a linear narrative.

The 5 Essential Ingredients

Research proposals can vary in style between institutions and disciplines, but here I’ll share with you a   handy 5-section structure   you can use. These 5 sections directly address the core questions we spoke about earlier, ensuring that you present a convincing proposal. If your institution already provides a proposal template, there will likely be substantial overlap with this, so you’ll still get value from reading on.

For each section discussed below, make sure you use headers and sub-headers (ideally, numbered headers) to help the reader navigate through your document, and to support them when they need to revisit a previous section. Don’t just present an endless wall of text, paragraph after paragraph after paragraph…

Top Tip:   Use MS Word Styles to format headings. This will allow you to be clear about whether a sub-heading is level 2, 3, or 4. Additionally, you can view your document in ‘outline view’ which will show you only your headings. This makes it much easier to check your structure, shift things around and make decisions about where a section needs to sit. You can also generate a 100% accurate table of contents using Word’s automatic functionality.

Ingredient #1 – Topic/Title Header

Your research proposal’s title should be your main research question in its simplest form, possibly with a sub-heading providing basic details on the specifics of the study. For example:

“Compliance with equality legislation in the charity sector: a study of the ‘reasonable adjustments’ made in three London care homes”

As you can see, this title provides a clear indication of what the research is about, in broad terms. It paints a high-level picture for the first-time reader, which gives them a taste of what to expect.   Always aim for a clear, concise title . Don’t feel the need to capture every detail of your research in your title – your proposal will fill in the gaps.

Need a helping hand?

Ingredient #2 – Introduction

In this section of your research proposal, you’ll expand on what you’ve communicated in the title, by providing a few paragraphs which offer more detail about your research topic. Importantly, the focus here is the   topic   – what will you research and why is that worth researching? This is not the place to discuss methodology, practicalities, etc. – you’ll do that later.

You should cover the following:

• An overview of the   broad area   you’ll be researching – introduce the reader to key concepts and language
• An explanation of the   specific (narrower) area   you’ll be focusing, and why you’ll be focusing there
• Your research   aims   and   objectives
• Your   research question (s) and sub-questions (if applicable)

Importantly, you should aim to use short sentences and plain language – don’t babble on with extensive jargon, acronyms and complex language. Assume that the reader is an intelligent layman – not a subject area specialist (even if they are). Remember that the   best writing is writing that can be easily understood   and digested. Keep it simple.

Note that some universities may want some extra bits and pieces in your introduction section. For example, personal development objectives, a structural outline, etc. Check your brief to see if there are any other details they expect in your proposal, and make sure you find a place for these.

Ingredient #3 – Scope

Next, you’ll need to specify what the scope of your research will be – this is also known as the delimitations . In other words, you need to make it clear what you will be covering and, more importantly, what you won’t be covering in your research. Simply put, this is about ring fencing your research topic so that you have a laser-sharp focus.

All too often, students feel the need to go broad and try to address as many issues as possible, in the interest of producing comprehensive research. Whilst this is admirable, it’s a mistake. By tightly refining your scope, you’ll enable yourself to   go deep   with your research, which is what you need to earn good marks. If your scope is too broad, you’re likely going to land up with superficial research (which won’t earn marks), so don’t be afraid to narrow things down.

Ingredient #4 – Literature Review

In this section of your research proposal, you need to provide a (relatively) brief discussion of the existing literature. Naturally, this will not be as comprehensive as the literature review in your actual dissertation, but it will lay the foundation for that. In fact, if you put in the effort at this stage, you’ll make your life a lot easier when it’s time to write your actual literature review chapter.

There are a few things you need to achieve in this section:

• Demonstrate that you’ve done your reading and are   familiar with the current state of the research   in your topic area.
• Show that   there’s a clear gap   for your specific research – i.e., show that your topic is sufficiently unique and will add value to the existing research.
• Show how the existing research has shaped your thinking regarding   research design . For example, you might use scales or questionnaires from previous studies.

When you write up your literature review, keep these three objectives front of mind, especially number two (revealing the gap in the literature), so that your literature review has a   clear purpose and direction . Everything you write should be contributing towards one (or more) of these objectives in some way. If it doesn’t, you need to ask yourself whether it’s truly needed.

Top Tip:  Don’t fall into the trap of just describing the main pieces of literature, for example, “A says this, B says that, C also says that…” and so on. Merely describing the literature provides no value. Instead, you need to   synthesise   it, and use it to address the three objectives above.

Ingredient #5 – Research Methodology

Now that you’ve clearly explained both your intended research topic (in the introduction) and the existing research it will draw on (in the literature review section), it’s time to get practical and explain exactly how you’ll be carrying out your own research. In other words, your research methodology.

In this section, you’ll need to   answer two critical questions :

• How   will you design your research? I.e., what research methodology will you adopt, what will your sample be, how will you collect data, etc.
• Why   have you chosen this design? I.e., why does this approach suit your specific research aims, objectives and questions?

In other words, this is not just about explaining WHAT you’ll be doing, it’s also about explaining WHY. In fact, the   justification is the most important part , because that justification is how you demonstrate a good understanding of research design (which is what assessors want to see).

Some essential design choices you need to cover in your research proposal include:

• Your intended research philosophy (e.g., positivism, interpretivism or pragmatism )
• What methodological approach you’ll be taking (e.g., qualitative , quantitative or mixed )
• The details of your sample (e.g., sample size, who they are, who they represent, etc.)
• What data you plan to collect (i.e. data about what, in what form?)
• How you plan to collect it (e.g., surveys , interviews , focus groups, etc.)
• How you plan to analyse it (e.g., regression analysis, thematic analysis , etc.)
• Ethical adherence (i.e., does this research satisfy all ethical requirements of your institution, or does it need further approval?)

This list is not exhaustive – these are just some core attributes of research design. Check with your institution what level of detail they expect. The “ research onion ” by Saunders et al (2009) provides a good summary of the various design choices you ultimately need to make – you can   read more about that here .

Don’t forget the practicalities…

In addition to the technical aspects, you will need to address the   practical   side of the project. In other words, you need to explain   what resources you’ll need   (e.g., time, money, access to equipment or software, etc.) and how you intend to secure these resources. You need to show that your project is feasible, so any “make or break” type resources need to already be secured. The success or failure of your project cannot depend on some resource which you’re not yet sure you have access to.

Another part of the practicalities discussion is   project and risk management . In other words, you need to show that you have a clear project plan to tackle your research with. Some key questions to address:

• What are the timelines for each phase of your project?
• Are the time allocations reasonable?
• What happens if something takes longer than anticipated (risk management)?
• What happens if you don’t get the response rate you expect?

A good way to demonstrate that you’ve thought this through is to include a Gantt chart and a risk register (in the appendix if word count is a problem). With these two tools, you can show that you’ve got a clear, feasible plan, and you’ve thought about and accounted for the potential risks.

Tip – Be honest about the potential difficulties – but show that you are anticipating solutions and workarounds. This is much more impressive to an assessor than an unrealistically optimistic proposal which does not anticipate any challenges whatsoever.

Final Touches: Read And Simplify

The final step is to edit and proofread your proposal – very carefully. It sounds obvious, but all too often poor editing and proofreading ruin a good proposal. Nothing is more off-putting for an assessor than a poorly edited, typo-strewn document. It sends the message that you either do not pay attention to detail, or just don’t care. Neither of these are good messages. Put the effort into editing and proofreading your proposal (or pay someone to do it for you) – it will pay dividends.

When you’re editing, watch out for ‘academese’. Many students can speak simply, passionately and clearly about their dissertation topic – but become incomprehensible the moment they turn the laptop on. You are not required to write in any kind of special, formal, complex language when you write academic work. Sure, there may be technical terms, jargon specific to your discipline, shorthand terms and so on. But, apart from those,   keep your written language very close to natural spoken language   – just as you would speak in the classroom. Imagine that you are explaining your project plans to your classmates or a family member. Remember, write for the intelligent layman, not the subject matter experts. Plain-language, concise writing is what wins hearts and minds – and marks!

Let’s Recap: Research Proposal 101

And there you have it – how to write your dissertation or thesis research proposal, from the title page to the final proof. Here’s a quick recap of the key takeaways:

• The purpose of the research proposal is to   convince   – therefore, you need to make a clear, concise argument of why your research is both worth doing and doable.
• Make sure you can ask the critical what, who, and how questions of your research   before   you put pen to paper.
• Title – provides the first taste of your research, in broad terms
• Introduction – explains what you’ll be researching in more detail
• Scope – explains the boundaries of your research
• Literature review – explains how your research fits into the existing research and why it’s unique and valuable
• Research methodology – explains and justifies how you will carry out your own research

Hopefully, this post has helped you better understand how to write up a winning research proposal. If you enjoyed it, be sure to check out the rest of the Grad Coach Blog . If your university doesn’t provide any template for your proposal, you might want to try out our free research proposal template .

Psst… there’s more!

This post is an extract from our bestselling short course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

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30 Comments

Thank you so much for the valuable insight that you have given, especially on the research proposal. That is what I have managed to cover. I still need to go back to the other parts as I got disturbed while still listening to Derek’s audio on you-tube. I am inspired. I will definitely continue with Grad-coach guidance on You-tube.

Thanks for the kind words :). All the best with your proposal.

First of all, thanks a lot for making such a wonderful presentation. The video was really useful and gave me a very clear insight of how a research proposal has to be written. I shall try implementing these ideas in my RP.

Once again, I thank you for this content.

I found reading your outline on writing research proposal very beneficial. I wish there was a way of submitting my draft proposal to you guys for critiquing before I submit to the institution.

Hi Bonginkosi

Thank you for the kind words. Yes, we do provide a review service. The best starting point is to have a chat with one of our coaches here: https://gradcoach.com/book/new/ .

Hello team GRADCOACH, may God bless you so much. I was totally green in research. Am so happy for your free superb tutorials and resources. Once again thank you so much Derek and his team.

You’re welcome, Erick. Good luck with your research proposal 🙂

thank you for the information. its precise and on point.

Really a remarkable piece of writing and great source of guidance for the researchers. GOD BLESS YOU for your guidance. Regards

Thanks so much for your guidance. It is easy and comprehensive the way you explain the steps for a winning research proposal.

Thank you guys so much for the rich post. I enjoyed and learn from every word in it. My problem now is how to get into your platform wherein I can always seek help on things related to my research work ? Secondly, I wish to find out if there is a way I can send my tentative proposal to you guys for examination before I take to my supervisor Once again thanks very much for the insights

Thanks for your kind words, Desire.

If you are based in a country where Grad Coach’s paid services are available, you can book a consultation by clicking the “Book” button in the top right.

Best of luck with your studies.

May God bless you team for the wonderful work you are doing,

If I have a topic, Can I submit it to you so that you can draft a proposal for me?? As I am expecting to go for masters degree in the near future.

Thanks for your comment. We definitely cannot draft a proposal for you, as that would constitute academic misconduct. The proposal needs to be your own work. We can coach you through the process, but it needs to be your own work and your own writing.

Best of luck with your research!

I found a lot of many essential concepts from your material. it is real a road map to write a research proposal. so thanks a lot. If there is any update material on your hand on MBA please forward to me.

GradCoach is a professional website that presents support and helps for MBA student like me through the useful online information on the page and with my 1-on-1 online coaching with the amazing and professional PhD Kerryen.

Thank you Kerryen so much for the support and help 🙂

I really recommend dealing with such a reliable services provider like Gradcoah and a coach like Kerryen.

Hi, Am happy for your service and effort to help students and researchers, Please, i have been given an assignment on research for strategic development, the task one is to formulate a research proposal to support the strategic development of a business area, my issue here is how to go about it, especially the topic or title and introduction. Please, i would like to know if you could help me and how much is the charge.

This content is practical, valuable, and just great!

Thank you very much!

Hi Derek, Thank you for the valuable presentation. It is very helpful especially for beginners like me. I am just starting my PhD.

This is quite instructive and research proposal made simple. Can I have a research proposal template?

Great! Thanks for rescuing me, because I had no former knowledge in this topic. But with this piece of information, I am now secured. Thank you once more.

I enjoyed listening to your video on how to write a proposal. I think I will be able to write a winning proposal with your advice. I wish you were to be my supervisor.

Dear Derek Jansen,

Thank you for your great content. I couldn’t learn these topics in MBA, but now I learned from GradCoach. Really appreciate your efforts….

From Afghanistan!

I have got very essential inputs for startup of my dissertation proposal. Well organized properly communicated with video presentation. Thank you for the presentation.

Wow, this is absolutely amazing guys. Thank you so much for the fruitful presentation, you’ve made my research much easier.

this helps me a lot. thank you all so much for impacting in us. may god richly bless you all

How I wish I’d learn about Grad Coach earlier. I’ve been stumbling around writing and rewriting! Now I have concise clear directions on how to put this thing together. Thank you!

Fantastic!! Thank You for this very concise yet comprehensive guidance.

Even if I am poor in English I would like to thank you very much.

Thank you very much, this is very insightful.

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17 Research Proposal Examples

A research proposal systematically and transparently outlines a proposed research project.

The purpose of a research proposal is to demonstrate a project’s viability and the researcher’s preparedness to conduct an academic study. It serves as a roadmap for the researcher.

The process holds value both externally (for accountability purposes and often as a requirement for a grant application) and intrinsic value (for helping the researcher to clarify the mechanics, purpose, and potential signficance of the study).

Key sections of a research proposal include: the title, abstract, introduction, literature review, research design and methods, timeline, budget, outcomes and implications, references, and appendix. Each is briefly explained below.

Watch my Guide: How to Write a Research Proposal

Get your Template for Writing your Research Proposal Here (With AI Prompts!)

Research Proposal Sample Structure

Title: The title should present a concise and descriptive statement that clearly conveys the core idea of the research projects. Make it as specific as possible. The reader should immediately be able to grasp the core idea of the intended research project. Often, the title is left too vague and does not help give an understanding of what exactly the study looks at.

Abstract: Abstracts are usually around 250-300 words and provide an overview of what is to follow – including the research problem , objectives, methods, expected outcomes, and significance of the study. Use it as a roadmap and ensure that, if the abstract is the only thing someone reads, they’ll get a good fly-by of what will be discussed in the peice.

Introduction: Introductions are all about contextualization. They often set the background information with a statement of the problem. At the end of the introduction, the reader should understand what the rationale for the study truly is. I like to see the research questions or hypotheses included in the introduction and I like to get a good understanding of what the significance of the research will be. It’s often easiest to write the introduction last

Literature Review: The literature review dives deep into the existing literature on the topic, demosntrating your thorough understanding of the existing literature including themes, strengths, weaknesses, and gaps in the literature. It serves both to demonstrate your knowledge of the field and, to demonstrate how the proposed study will fit alongside the literature on the topic. A good literature review concludes by clearly demonstrating how your research will contribute something new and innovative to the conversation in the literature.

Research Design and Methods: This section needs to clearly demonstrate how the data will be gathered and analyzed in a systematic and academically sound manner. Here, you need to demonstrate that the conclusions of your research will be both valid and reliable. Common points discussed in the research design and methods section include highlighting the research paradigm, methodologies, intended population or sample to be studied, data collection techniques, and data analysis procedures . Toward the end of this section, you are encouraged to also address ethical considerations and limitations of the research process , but also to explain why you chose your research design and how you are mitigating the identified risks and limitations.

Timeline: Provide an outline of the anticipated timeline for the study. Break it down into its various stages (including data collection, data analysis, and report writing). The goal of this section is firstly to establish a reasonable breakdown of steps for you to follow and secondly to demonstrate to the assessors that your project is practicable and feasible.

Budget: Estimate the costs associated with the research project and include evidence for your estimations. Typical costs include staffing costs, equipment, travel, and data collection tools. When applying for a scholarship, the budget should demonstrate that you are being responsible with your expensive and that your funding application is reasonable.

Expected Outcomes and Implications: A discussion of the anticipated findings or results of the research, as well as the potential contributions to the existing knowledge, theory, or practice in the field. This section should also address the potential impact of the research on relevant stakeholders and any broader implications for policy or practice.

References: A complete list of all the sources cited in the research proposal, formatted according to the required citation style. This demonstrates the researcher’s familiarity with the relevant literature and ensures proper attribution of ideas and information.

Appendices (if applicable): Any additional materials, such as questionnaires, interview guides, or consent forms, that provide further information or support for the research proposal. These materials should be included as appendices at the end of the document.

Research Proposal Examples

Research proposals often extend anywhere between 2,000 and 15,000 words in length. The following snippets are samples designed to briefly demonstrate what might be discussed in each section.

1. Education Studies Research Proposals

See some real sample pieces:

• Assessment of the perceptions of teachers towards a new grading system
• Does ICT use in secondary classrooms help or hinder student learning?
• Digital technologies in focus project
• Urban Middle School Teachers’ Experiences of the Implementation of
• Restorative Justice Practices
• Experiences of students of color in service learning

Consider this hypothetical education research proposal:

The Impact of Game-Based Learning on Student Engagement and Academic Performance in Middle School Mathematics

Abstract: The proposed study will explore multiplayer game-based learning techniques in middle school mathematics curricula and their effects on student engagement. The study aims to contribute to the current literature on game-based learning by examining the effects of multiplayer gaming in learning.

Introduction: Digital game-based learning has long been shunned within mathematics education for fears that it may distract students or lower the academic integrity of the classrooms. However, there is emerging evidence that digital games in math have emerging benefits not only for engagement but also academic skill development. Contributing to this discourse, this study seeks to explore the potential benefits of multiplayer digital game-based learning by examining its impact on middle school students’ engagement and academic performance in a mathematics class.

Literature Review: The literature review has identified gaps in the current knowledge, namely, while game-based learning has been extensively explored, the role of multiplayer games in supporting learning has not been studied.

Research Design and Methods: This study will employ a mixed-methods research design based upon action research in the classroom. A quasi-experimental pre-test/post-test control group design will first be used to compare the academic performance and engagement of middle school students exposed to game-based learning techniques with those in a control group receiving instruction without the aid of technology. Students will also be observed and interviewed in regard to the effect of communication and collaboration during gameplay on their learning.

Timeline: The study will take place across the second term of the school year with a pre-test taking place on the first day of the term and the post-test taking place on Wednesday in Week 10.

Budget: The key budgetary requirements will be the technologies required, including the subscription cost for the identified games and computers.

Expected Outcomes and Implications: It is expected that the findings will contribute to the current literature on game-based learning and inform educational practices, providing educators and policymakers with insights into how to better support student achievement in mathematics.

2. Psychology Research Proposals

See some real examples:

• A situational analysis of shared leadership in a self-managing team
• The effect of musical preference on running performance
• Relationship between self-esteem and disordered eating amongst adolescent females

Consider this hypothetical psychology research proposal:

The Effects of Mindfulness-Based Interventions on Stress Reduction in College Students

Abstract: This research proposal examines the impact of mindfulness-based interventions on stress reduction among college students, using a pre-test/post-test experimental design with both quantitative and qualitative data collection methods .

Introduction: College students face heightened stress levels during exam weeks. This can affect both mental health and test performance. This study explores the potential benefits of mindfulness-based interventions such as meditation as a way to mediate stress levels in the weeks leading up to exam time.

Literature Review: Existing research on mindfulness-based meditation has shown the ability for mindfulness to increase metacognition, decrease anxiety levels, and decrease stress. Existing literature has looked at workplace, high school and general college-level applications. This study will contribute to the corpus of literature by exploring the effects of mindfulness directly in the context of exam weeks.

Research Design and Methods: Participants ( n= 234 ) will be randomly assigned to either an experimental group, receiving 5 days per week of 10-minute mindfulness-based interventions, or a control group, receiving no intervention. Data will be collected through self-report questionnaires, measuring stress levels, semi-structured interviews exploring participants’ experiences, and students’ test scores.

Timeline: The study will begin three weeks before the students’ exam week and conclude after each student’s final exam. Data collection will occur at the beginning (pre-test of self-reported stress levels) and end (post-test) of the three weeks.

Expected Outcomes and Implications: The study aims to provide evidence supporting the effectiveness of mindfulness-based interventions in reducing stress among college students in the lead up to exams, with potential implications for mental health support and stress management programs on college campuses.

3. Sociology Research Proposals

• Understanding emerging social movements: A case study of ‘Jersey in Transition’
• The interaction of health, education and employment in Western China
• Can we preserve lower-income affordable neighbourhoods in the face of rising costs?

Consider this hypothetical sociology research proposal:

The Impact of Social Media Usage on Interpersonal Relationships among Young Adults

Abstract: This research proposal investigates the effects of social media usage on interpersonal relationships among young adults, using a longitudinal mixed-methods approach with ongoing semi-structured interviews to collect qualitative data.

Introduction: Social media platforms have become a key medium for the development of interpersonal relationships, particularly for young adults. This study examines the potential positive and negative effects of social media usage on young adults’ relationships and development over time.

Literature Review: A preliminary review of relevant literature has demonstrated that social media usage is central to development of a personal identity and relationships with others with similar subcultural interests. However, it has also been accompanied by data on mental health deline and deteriorating off-screen relationships. The literature is to-date lacking important longitudinal data on these topics.

Research Design and Methods: Participants ( n = 454 ) will be young adults aged 18-24. Ongoing self-report surveys will assess participants’ social media usage, relationship satisfaction, and communication patterns. A subset of participants will be selected for longitudinal in-depth interviews starting at age 18 and continuing for 5 years.

Timeline: The study will be conducted over a period of five years, including recruitment, data collection, analysis, and report writing.

Expected Outcomes and Implications: This study aims to provide insights into the complex relationship between social media usage and interpersonal relationships among young adults, potentially informing social policies and mental health support related to social media use.

4. Nursing Research Proposals

• Does Orthopaedic Pre-assessment clinic prepare the patient for admission to hospital?
• Nurses’ perceptions and experiences of providing psychological care to burns patients
• Registered psychiatric nurse’s practice with mentally ill parents and their children

Consider this hypothetical nursing research proposal:

The Influence of Nurse-Patient Communication on Patient Satisfaction and Health Outcomes following Emergency Cesarians

Abstract: This research will examines the impact of effective nurse-patient communication on patient satisfaction and health outcomes for women following c-sections, utilizing a mixed-methods approach with patient surveys and semi-structured interviews.

Introduction: It has long been known that effective communication between nurses and patients is crucial for quality care. However, additional complications arise following emergency c-sections due to the interaction between new mother’s changing roles and recovery from surgery.

Literature Review: A review of the literature demonstrates the importance of nurse-patient communication, its impact on patient satisfaction, and potential links to health outcomes. However, communication between nurses and new mothers is less examined, and the specific experiences of those who have given birth via emergency c-section are to date unexamined.

Research Design and Methods: Participants will be patients in a hospital setting who have recently had an emergency c-section. A self-report survey will assess their satisfaction with nurse-patient communication and perceived health outcomes. A subset of participants will be selected for in-depth interviews to explore their experiences and perceptions of the communication with their nurses.

Timeline: The study will be conducted over a period of six months, including rolling recruitment, data collection, analysis, and report writing within the hospital.

Expected Outcomes and Implications: This study aims to provide evidence for the significance of nurse-patient communication in supporting new mothers who have had an emergency c-section. Recommendations will be presented for supporting nurses and midwives in improving outcomes for new mothers who had complications during birth.

5. Social Work Research Proposals

• Experiences of negotiating employment and caring responsibilities of fathers post-divorce
• Exploring kinship care in the north region of British Columbia

Consider this hypothetical social work research proposal:

The Role of a Family-Centered Intervention in Preventing Homelessness Among At-Risk Youthin a working-class town in Northern England

Abstract: This research proposal investigates the effectiveness of a family-centered intervention provided by a local council area in preventing homelessness among at-risk youth. This case study will use a mixed-methods approach with program evaluation data and semi-structured interviews to collect quantitative and qualitative data .

Introduction: Homelessness among youth remains a significant social issue. This study aims to assess the effectiveness of family-centered interventions in addressing this problem and identify factors that contribute to successful prevention strategies.

Literature Review: A review of the literature has demonstrated several key factors contributing to youth homelessness including lack of parental support, lack of social support, and low levels of family involvement. It also demonstrates the important role of family-centered interventions in addressing this issue. Drawing on current evidence, this study explores the effectiveness of one such intervention in preventing homelessness among at-risk youth in a working-class town in Northern England.

Research Design and Methods: The study will evaluate a new family-centered intervention program targeting at-risk youth and their families. Quantitative data on program outcomes, including housing stability and family functioning, will be collected through program records and evaluation reports. Semi-structured interviews with program staff, participants, and relevant stakeholders will provide qualitative insights into the factors contributing to program success or failure.

Timeline: The study will be conducted over a period of six months, including recruitment, data collection, analysis, and report writing.

Budget: Expenses include access to program evaluation data, interview materials, data analysis software, and any related travel costs for in-person interviews.

Expected Outcomes and Implications: This study aims to provide evidence for the effectiveness of family-centered interventions in preventing youth homelessness, potentially informing the expansion of or necessary changes to social work practices in Northern England.

Research Proposal Template

Get your Detailed Template for Writing your Research Proposal Here (With AI Prompts!)

This is a template for a 2500-word research proposal. You may find it difficult to squeeze everything into this wordcount, but it’s a common wordcount for Honors and MA-level dissertations.

Your research proposal is where you really get going with your study. I’d strongly recommend working closely with your teacher in developing a research proposal that’s consistent with the requirements and culture of your institution, as in my experience it varies considerably. The above template is from my own courses that walk students through research proposals in a British School of Education.

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 50 Durable Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 100 Consumer Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 30 Globalization Pros and Cons

8 thoughts on “17 Research Proposal Examples”

Very excellent research proposals

very helpful

Very helpful

Dear Sir, I need some help to write an educational research proposal. Thank you.

Hi Levi, use the site search bar to ask a question and I’ll likely have a guide already written for your specific question. Thanks for reading!

very good research proposal

Thank you so much sir! ❤️

Very helpful 👌

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Top 10 Data Analysis Research Proposal Templates with Examples and Samples

Himani Khatri

In a world awash with data, the real challenge lies not in the abundance of information but in deciphering its true meaning, making sense of the chaos, and addressing pressing real-world problems. If you're a researcher or student, you know the struggle: the pain points of grappling with data quality, precision, and relevance. It's these very challenges that underscore the critical importance of crafting a well-structured data analysis research proposal.

Think of it as your toolkit, a roadmap to navigate the complexities of data-driven research and turn information into solutions. In this blog, we're here to help you master the art of creating a data analysis research proposal, providing you with the key to unlock the answers to those nagging questions, and offer solutions (Our editable templates) to problems that keep you up at night.

As we start this journey, let's draw inspiration from two illustrious examples, Google Flu Trends and Netflix's Recommendation Algorithm, which have not only captured the limelight but have tackled data-related pain points and transformed them into remarkable solutions. These examples will serve as guiding stars as we navigate the intricacies of data analysis to craft proposals that address real-world issues head-on.

Google Flu Trends : Conquering the Challenge of Data Accuracy

Imagine having the power to predict flu outbreaks with uncanny precision. Google Flu Trends did just that, tapping into the vast sea of search queries. But it wasn't just about innovation; it was also about recognizing the persistent pain point of data accuracy and modeling. The project revealed that behind every data analysis success story lies the challenge of ensuring data quality and building models that stand up to the rigorous demands of real-world problems.

Netflix's Recommendation Algorithm : Navigating the Data Overload Dilemma

In the world of entertainment, where options seem endless, Netflix's Recommendation Algorithm emerged as a winner. It tackled the overwhelming pain point of information overload by leveraging data to understand users better. The result? A recommendation system that not only improved user satisfaction but also demonstrated how data analysis can help individuals navigate through the ever-growing sea of choices and make their lives easier.

In these two case studies, we uncover the real-world challenges that data analysis can address, from accuracy dilemmas to information overload.

Let's explore the research proposal presentation templates now!

Template 1: Data Analysis in Research Proposal

Click Here to Download

Introducing this cover slide of the proposal that has been professionally designed and sets the stage for your entire research proposal. With ample space for an image, it captures your audience's attention from the start. Your proposal's credentials, both for the recipient and the preparer, can be displayed. Both researchers and professionals can take assistance to streamline the presentation creation process, leaving you more time to focus on your data analysis. Make a lasting impression and get your proposal noticed with this polished, easy-to-use template.

Template 2: Cover Letter for Research Data Analysis Proposal

Introducing this Cover Letter Slide, which will help you make a lasting impression in the world of research and analytics. We understand the importance of clear and concise communication in proposals. Our professionally crafted slide provides a perfect introduction, addressing your customers and outlining your company's objectives. Say goodbye to the hassle of creating proposals from scratch – with our ready-made slide, you can simply insert your details and be on your way to success. This cover letter helps you state that your experience and expertise will help your audience achieve their goals effortlessly. Don't miss this opportunity – grab this proposal slide and make a strong, confident start in the world of data analytics.

Template 3 – Project Context and Objectives of Research Data Analysis Proposal

This slide simplifies the process of impressing your clients. It explains your project's context and objectives, leaving a lasting impact on your audience.

Project Context: We provide a clear and concise space for explaining the background and significance of your research, setting the stage for your proposal.

Project Objectives: Clearly outline your research goals and what you aim to achieve, ensuring everyone understands your mission.

Make your research proposal shine with this template at your disposal.

Template 4: Scope of Work for Research Data Analysis Proposal

This slide outlines your research data analysis journey, making client presentations a breeze. Our scope of work slide covers all the essentials: Acquisition & Extraction, Examination, Cleaning, Transformation, Exploration, and Analysis, leading to the grand finale - Presenting and Sharing your findings. With clear and easy-to-understand visuals, impress your clients and streamline your workflow.

Template 5: Plan of Action for Research Data Analysis Proposal

Are you looking to present your research data analysis plan with clarity and professionalism? Our ready-made PowerPoint slide has got you covered. This user-friendly template features a visual diagram illustrating the entire process, from data collection through pre-processing, analysis, and classification. With easy-to-understand icons and clear labels, you can effectively convey your plan to your audience.

Template 6: Timeline for Research Data Analysis Project

Designed with simplicity, this timeline slide offers a user-friendly layout to help you convey complex ideas easily. It covers every crucial step of your analysis journey, from tackling business issues to final presentation. With vibrant visuals and customizable elements, you can effortlessly illustrate data understanding, preparation, exploratory analysis, validation, and visualization. Get it today!

Template 7: Key Deliverables for Research Data Analysis Proposal

With clear, concise visuals, this slide presents your key deliverables. From ‘Decision Mapping’ that outlines your project's path to ‘Analysis and Design’ for robust strategies, and ‘Implementation’ for real-world action, it's all here. Even better, it highlights ‘Ongoing Steps’ for sustained success. Why waste time on complex slides when you can have this ready-made gem? Elevate your presentations and win your audience over with this template at your disposal.

Template 8: Why Our Data Analytics Company?

This slide helps you showcase why people should choose your company rather than your competitors. Elucidate what makes your organization stand out from the rest by taking assistance of this readily-available PowerPoint slide. 

It lists down the strength that keeps your firm on the top in comparison with your rivals.

Some of the strengths mentioned in the slide are:

• Reduced churn rate
• Reduced operational cost
• Increased revenue
• Faster data analysis reporting

Template 9: Services Offered by Data Analytics Company 

This slide presents the services offered by data analysis company in a clear and precise way. Get your hands on this slide to present your offerings. The template encapsulates services like data collection services, data quality assess, data integration, policy analytics, social media and digital outreach, enterprise analytics, and more.

Template 10: Team Structure of Data Analysis Company

The slide presents team structure of data analytics company in a comprehensive format. A hierarchy chart makes it easy for organization to showcase their talented staff and the driving forces behind their firm’s success, this is where this template comes into assistance. Put your hands on this template to present head of advanced analytics, COE Support office, demand management, analytics development, analytics support, etc.

These templates are your one-stop solution for crafting compelling Research Data Analysis Proposals.

With a subscription to our service, you gain access to an extensive library of ready-made PowerPoint templates that will save you time and effort. But that's not all – if you require a personalized touch, our team can also design a custom proposal that perfectly aligns with your unique needs.

Why wait? Join our community of satisfied customers and supercharge your research endeavors today.

Subscribe now and get your hands on impactful presentations!

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Bridging Clinical Investigators and Statisticians: Writing the Statistical Methodology for a Research Proposal

Introduction.

Clinical research is judged to be valid not by the results but how it is designed and conducted. The cliché of ‘do it right or do it over’ is particularly apt in clinical research.

One of the questions a clinical investigator frequently asks in planning clinical research is “Do I need a statistician as part of my clinical research team?” The answer is “Yes!” since a statistician can help to optimize design, analysis and interpretation of results, and drawing conclusions. When developing a clinical research proposal, how early in the process should the clinical investigator contact the statistician? Answer - it is never too early. Statistics cannot rescue a poorly designed protocol after the study has begun. A statistician can be a valuable member of a clinical research team and often serves as a co-investigator. Large multicenter projects such as Phase III randomized clinical trials for drug approval by a regulatory agency nearly always have a statistician (or several) on their team. However, smaller, typically single center studies may also require rigorous statistical methodology in design and analysis. These studies are often devised by young clinical investigators launching their clinical research career who may have not collaborated with a statistician. Many clinical investigators are familiar with the statistical role in the analysis of research data 1 , but researchers may not be as aware of the role of a statistician in designing clinical research and developing the study protocol. In this paper we discuss topics and situations that clinical investigators and statisticians commonly encounter while planning a research study and writing the statistical methods section. We stress the importance of having the statistical methodology planned well in advance of conducting the clinical research study. Working in conjunction with a statistician can also be a key training opportunity for the clinical investigator beginning a clinical research career.

GETTING STARTED ON THE STATISTICAL ANALYSIS PLAN

Why work with a statistician.

The study design, sample size, and statistical analysis must be able to properly evaluate the research hypothesis set forth by the clinical investigator. Otherwise, the consequences of a poorly developed statistical approach may result in a failure to obtain extramural funding and result in a flawed clinical study that cannot adequately test the desired hypotheses. Statisticians provide design advice and develop the statistical methods that best correspond to the research hypothesis. For the planning of a clinical study, a statistician can provide valuable information on key design points as summarized in Table 1 . The statistician can discuss with the clinical investigators questions such as: Is the design valid? Overly ambitious? Will the data be analyzable?

The role of the statistician in developing the statistical plan

Very early in the planning stages, it is important to send the statistician a draft of the proposal. Any protocol changes may affect the required sample size and analysis plans so it is important to meet with the statistician throughout the planning stages and later if modifications have been made to the study design. Before the statistical section can be developed, what information does the statistician need? Questions from a statistician concerning design, power and sample size, and analysis may include:

• What is the research hypothesis?
• What is the type of study design?
• What is the most important measurement (primary outcome variable)?
• What is the type of variable and unit of measurement?
• What is a clinically meaningful difference for the primary outcome?
• How many subjects can be recruited or observed within a study period? How many groups or treatment arms are to be included in your design?
• Will there be an equal number of participants or observations in each group? i.e., what is the allocation ratio?
• How many total evaluations and measurements?
• For repeated measurements, what is the measurement interval?

You are not expected to have all the answers at your first meeting and ongoing conversations with the statistician can serve to develop these ideas. Eventually, the answers to these questions comprise the justification for the design selected, provide the basis for the sample size estimate, and drive the choice of statistical analysis. A brief consultation with a statistician will not be adequate to address these issues. The interaction with a statistician to construct the statistical section is not usually one meeting, email, or phone call. It is a process that will help you think through the design of your study. This is also an excellent opportunity to ask questions and enhance your statistical education. Additionally, the exchange of ideas is beneficial to the statistician who will better appreciate the clinical research question. The discussions with a statistician could lead to changes in study design, such as proposing a smaller, more focused study design to collect preliminary data.

A general outline of the statistical methods section is shown in Table 2 . There may be deviations from this format depending on the particular study design. The statistical write-up is rarely less than one page and may total several pages. Although some clinical investigators trained in statistics do prepare this section, more commonly the statistician constructs and writes up the statistical methods section for grants and protocols in close collaboration with the investigators. However, it is important that clinical investigators develop a conceptual understanding of the proposed statistical methodology. Take advantage of any study design and biostatistics classes offered at your institutions to make statistical collaborations more fruitful.

Outline of the statistical methods section

STUDY DESIGN

Type of design.

Before the statistical section can progress, the study design must be known. Study designs that are commonly used in clinical research include case-control, cohort, randomized controlled design, crossover, and factorial designs. A randomized controlled trial has many features but most commonly incorporates what is called a parallel group design where individuals are randomly assigned to a particular treatment or intervention group. In a crossover study, the subject participates in more than one study intervention phase, ideally studied in a random sequence, such as comparing triglyceride responses within the same individual on a low fat versus a high fat diet.

How do we select participants for the study? There are many types of sampling procedures, the basis of which is to avoid or reduce bias. Bias can be defined as ”a systematic tendency to produce an outcome that differs from the underlying truth”. 2 Although true randomness is the goal of a sampling, it is generally not achievable. The study subjects are not usually selected at random to participate in clinical research. Instead, in most clinical trials, the “random” element in randomization is that the consented subjects are assigned by chance to a particular treatment or intervention. The clinical inclusion and exclusion criteria coupled with informed consent will determine who will be the study participants and, ultimately, to what population the study results will be generalizable.

Sample size

With the study design and the make-up of the study sample determined, the sample size estimates can be obtained. Fundamental to estimating sample size are the concepts of statistical hypothesis testing, type I error, type II error, and power ( Table 3 ). In planning clinical research it is necessary to determine the number of subjects to be required so that the study achieves sufficient statistical power to detect the hypothesized effect. If the reader is not familiar with the concept of statistical hypothesis testing, introductory biostatistics texts and many web sites cover this topic. Briefly, in trials to demonstrate improved efficacy of a new treatment over placebo/standard treatments, the null hypothesis is that there is no difference between treatments and the alternative hypothesis is that there is a treatment difference. The research hypothesis usually corresponds to the alternative hypothesis which represents a minimal meaningful difference in clinical outcomes. Statistically, we either 1) reject the null hypothesis in favor of the alternative hypothesis or 2) we fail to reject the null hypothesis.

Definitions for statistical hypothesis testing

Typically, the sample size is computed to provide a fixed level of power under a specified alternative hypothesis. Power is an important consideration for several reasons. Low power can cause a true difference in clinical outcomes between study groups to go undetected. However, too much power may yield statistically significant results that are not meaningfully different to clinicians. The probability of Type I error (α) of 0.05 (two-sided) and power of 0.80 and 0.90 have been widely used for the sample size estimation in clinical trials. The sample size estimate will also allow the estimation of the total cost of the proposed study.

A clinical trial that is conducted without attention to sample size or power information takes the risks of either failing to detect clinically meaningful differences (Type II error) due to not enough subjects or taking an unnecessarily excessive number of samples for a study. Both cases fail to adhere to the Ethical Guidelines of the American Statistical Association which says “Avoid the use of excessive or inadequate number of research subjects by making informed recommendations for study size”. 3

What information is needed to calculate power and sample size?

The components that most sample size programs require for input include:

• Choose Type I error (alpha)
• Choose Power
• Choose clinical outcome variable and effect size (difference between means, proportions, survival times, regression parameters)
• Variation estimate
• Allocation ratio

Clinical outcome measures

Clearly describe the clinical outcomes that will be analyzed to the statistician. The variable type ( Table 4 ) and distribution of the primary outcome measurement must be defined before sample size and power calculations can proceed. The sample size estimates are mainly needed for the primary outcome. However, providing power estimates for secondary outcomes is often helpful to reviewers.

Variable types and derivations to be described in the statistical analysis plan

Effect size

As an example, suppose a parallel group study is being designed to compare systolic blood pressure between two treatments and the investigators want to be able to detect a mean 10 mm Hg difference between groups. This 10 mm Hg difference is referred to as the effect size, detectable difference, or minimal expected difference.

How is the effect size determined?

Choose an effect size that is based on clinical knowledge of the primary endpoint. A sample size that ‘worked’ in a published paper is no guarantee of success in a different setting. The selected effect size is unique to your study intervention, the specific type of participants in your study sample, and perhaps an aspect of the outcome measurement that is unique to your clinic or laboratory. 4

The investigator and statistician examine the literature, the investigator’s own past research, or a combination of the above to determine a study effect size. To investigate the difference in mean blood pressure between two treatments, the effect size options might be 2 mm Hg, 6 mm Hg, 10 mm Hg or 20 mm Hg. Which of these differences do you need to have the ability to detect? This is a clinical question, not a statistical question. Effect size is a measure of the magnitude of the treatment effect and represents a clinically or biologically important difference. Choosing a 20 mm Hg effect size yields a smaller sample size than a 10 mm Hg effect size since it is easier to statistically detect the larger difference. However, an effect size of 10 mm Hg or smaller magnitude may be more a realistic treatment effect and less likely to result in a flawed or wasted study.

Variation estimates for sample size calculations

In addition to effect size, we may need to estimate how much the outcome varies from person to person. For continuous variables, the variation estimate is often in the form of a standard deviation. If the hypothesized difference in systolic blood pressure is an effect size of 10 mm Hg, a study with a blood pressure standard deviation of 22 mm Hg will have lower power than a study where the standard deviation is 14 mm Hg. For a continuous outcome such as blood pressure, a measure of the variation is another part of the formula needed to compute the sample size. An estimate of variation can be derived from a literature search or from the investigator’s preliminary data. Obtaining this information can be a challenge for both the clinical investigator and statistician.

Table 5 shows sample sizes scenarios for detecting differences in blood pressure when comparing two treatments based on a t-test. A standard deviation of 14 mm Hg is chosen to estimate the variation. Sample sizes are calculated for power of 0.80 and 0.90 at the two-sided 0.05 significance level. Notice that the smaller effect sizes require a larger sample size and that the sample size increases as the power increases from 0.80 to 0.90.

Scenarios for choosing sample size

Determining a reasonable and affordable sample size estimate is a team effort. There are practical issues such as budgets or recruitment limitations that may come into play. A too large sample size could preclude the ability to conduct the research. The research team will assess scenarios with varying detectable differences and power as seen in Table 5 (calculations performed using PS power 5 available at the website < http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize >). Typically a scenario can be worked out which is both clinically and statistically viable.

The elements of sample size calculations presented here pertain to relatively simple designs. Cluster samples or family data need special statistical adjustments. For a longitudinal or repeated measures design, the correlation between the repeated measurements is incorporated into the sample size calculations. 6 , 7

Do all studies need sample size and power estimates?

Pilot studies.

Pilot studies may not need a power analysis since they are more about testing the protocol than testing a hypothesis. 8 Sometimes there are no preliminary data and thus pilot data must be obtained to provide estimates for designing for a more definitive study. However, calling a study a pilot study to avoid power analyses and to keep the sample small is misrepresentation. 8

Sample size calculations are necessary when the study goal is precision instead of power. The goal may be to describe the precision of a proportion or mean or other statistic that is to be estimated from our sample. Precision in this context is based upon finding a suitably narrow confidence interval for the statistic of interest, such that the lower and upper limits of the confidence interval include a clinically meaningful range of values. We may want to know how many subjects are required to be 95% confident that an interval contains the true, but unknown, value. For example, how many subjects are needed for 10% precision if we expect a 30% allele prevalence in a genetic study? Instead of power, we estimate the sample size for the desired precision based on a single proportion of 0.30 and summarize by stating “With 80 subjects, the precision for a 30% allele prevalence rate is approximately 10% (95% confidence interval: 21% to 40%).” If greater precision is desirable then the sample size is increased accordingly.

Accounting for attrition

Withdrawal and dropout are unwelcome realities of clinical research. Missing data in clinical trials or repeated measurement studies are inevitable. Consider missing data issues when designing, planning and conducting studies to minimize missing data impact. Sample size estimates are finalized by adjusting for attrition based upon the anticipated number of dropouts.

Randomization plan

Random allocation of subjects to study groups is fundamental to the clinical trial design. Randomization, which is a way to reduce bias, involves random allocation of the participants to the treatment groups. If investigators compare a new treatment against a standard treatment, the study subjects are allocated to one of these treatments by a random process. A general description of the randomization approach may be introduced in the clinical methods section of the proposal, for example, “Treatment assignment will be determined using stratified, blocked randomization”. Specific randomization details will need to be elaborated upon in the statistical methods section, including how the allocation procedure will be implemented, e.g., via computer programs, web site, lists, or sealed envelopes. If stratification is deemed necessary, include in the proposal a description of each stratification variable and the number of levels for each stratum, for instance, gender (male, female), diabetes (type 1, type 2). However, keep the number of strata and stratum levels minimal. 9 Discuss the advantages and disadvantages of the various allocation approaches with the study statistician.

Knowledge of the treatment assignment might influence how much of a dosage change is made to a study treatment or how an adverse event is assessed. Blinding or masking is another component of study design used to try to eliminate such bias. 10 In a double-blind randomized trial, neither the study subjects nor the clinical investigators know the treatment assignment.

Describe the planned blinding scheme. For example, “This is a double-blind randomized study to investigate the effect of propranolol versus no propranolol on the incidences of total mortality and of total mortality plus nonfatal myocardial infarction in 158 older patients with CHF and prior myocardial infarction.” Specify who is to be blinded and the steps that will be taken to maintain the blind. It is important that evaluators such as a radiologists, pathologists, or lab personnel who have no direct contact with the study subjects remain blinded to treatment assignments.

It may be impossible or difficult to use the double-blind procedures in some clinical trials. For example, it is not feasible to design a double-blind clinical trial for the comparison of surgical and non-surgical interventions. Or, blinding might not be completely successful; study personnel may be inadvertently alerted as to the probable treatment assignment due to the occurrence of a specific adverse event. If blinding is not feasible, offer an explanation for lack of blinding procedures in the research proposal.

STATISTICAL ANALYSIS METHODOLOGY

The statistical analysis methods for analyzing the study outcomes are to be carefully detailed. Specifying these methods in advance is another way to minimize bias and maintain the integrity of the analysis. Any changes to the statistical methods must be justified and decided upon before the blind is broken. 11 In the statistical analysis plan not only must the statistical hypotheses to be tested be described and justified but we also detail which subjects and observations will be included or excluded in each analysis.

Analysis data sets

Intention-to-treat analysis

It is crucial to define the primary sample of subjects analyzed in the reporting of clinical trial results. Defined in Table 6 , intention-to-treat (ITT) and per-protocol analyses are commonly reported in medical literature result sections. For a randomized study, intention-to-treat analysis is the gold standard for the primary analysis and the intention-to-treat principle is regarded as the most appropriate criteria for the assessment of a new therapy by the Food and Drug Administration and the National Institute of Health. 12 An intention-to-treat data set includes all randomized subjects, whether or not they were compliant or completed the study. Adhering to the ITT principle mirrors what occurs in clinical practice where a patient may discontinue a medication or miss a clinic appointment. This avoids biases that can result from dropouts and missing data. However, the missing data must not bias the treatment comparisons 13 , otherwise the statistics may not be valid. This type of bias could occur if the dropouts or missed study visits are related to a particular treatment group and are not observed equally across all of the treatments.

From ICH E9: Guidance for Industry - E9 Statistical Principles for Clinical Trials, U.S. Department of Health and Human Services, Food and Drug Administration, September 1998

A true intention-to-treat data set may not be attainable in all clinical trials. There might be no post-randomization or post-treatment data for a study subject who withdraws from the study at the initial study visit. Then the primary analysis might consist of all subjects who took at least one treatment dose or had at least one follow-up visit. 11 Anticipate these possibilities as the study is designed and specify in the statistical analysis plan which subjects and observations will comprise the “full analysis set”. Pre-specification of these data sets prior to statistical analysis is imperative.

Per-protocol analysis

It may be of clinical interest to plan an analysis set which consists of only ‘completers’ or ‘compliers’. A per-protocol analysis, defined in Table 6 , is more likely to be planned as secondary analyses. If the per-protocol analysis results are not consistent with the intention-to-treat analysis results, then closely examine the reasons behind any discrepancy.

Statistical analysis

The statistical analysis plan is driven by the research questions, the study design, and the type of the outcome measurements. The analysis plan includes a detailed description of statistical testing for each of the variables in the Specific Aim(s). If several Specific Aims are proposed, we write an analysis plan for each Specific Aim. Plan descriptive analyses for each group or planned subgroup. If subjects were randomly assigned to groups, it is expected that there will be a description of subject characteristics that include demographic information as well as baseline measurements or co-morbid conditions. Specify anticipated data transformations that may be needed to meet analysis assumptions and describe derived variables to be created such as area under the curve. Incorporate confidence intervals in the analysis plan for reporting treatment effects. Confidence limits are much more informative to the reader than are p-values alone. 14

Statistical details and terminology are not intended to be an obstacle for a young investigator. Instead this is where the statistical expert can be a valuable resource to help the investigators use the appropriate statistical methods and language that address the research hypotheses. Brief statistical analysis descriptions are shown in Table 7 for a randomized study and a longitudinal cohort study. In addition to the general methodology of Table 7 , we explain in the statistical methods section how statistical assumptions or model diagnostics will be evaluated. Describe the hypotheses to be tested with the corresponding statistical tests for the primary, secondary, and exploratory analyses. In the medical literature, statistical analyses such as chi-square and t-tests, analysis of variance, regression modeling, and various nonparametric tests are common. However, the statistician is happy to advise whether these traditional methods are appropriate for the research question at hand or if other approaches would be more suitable.

Statistical analysis plans

Statistics, like medicine, is a large and diverse field; hence statisticians have specific areas of expertise. Some proposals may require one statistician for the design and analysis of medical imaging studies and another statistician for design and analysis of a microarray study. Often a proposal specifies one statistician as the study statistician and another statistician to serve on a Data and Safety Monitoring Board.

Interim analysis

Conducting a planned interim analysis in an ongoing clinical trial can be beneficial for scientific, economic, and ethical reasons. 15 Formal interim analyses include stopping rules for terminating the study early if a treatment shows futility or clear benefit or harm. The termination of the estrogen plus progestin treatment arm of the Women’s Health Initiative clinical trial in 2002 16 when the treatment risks exceeded benefits demonstrates the strong clinical impact of interim analyses. However, interim analyses are not to be undertaken lightly. Taking unplanned repeated looks at accumulating data is problematic. First, it raises the multiple testing issue so that adjustments to control the overall Type I error rate are necessary. Second, the results can interfere with the conduct of the remainder of the study, creating bias. Pocock 17 and O’Brien & Fleming 18 authored the classic approaches for defining statistical stopping rules. The alpha spending function described by DeMets and Lan 19 provides some flexibility for the timing of interim analyses as well as controlling the Type I error rate. Clinical investigators must seriously consider what decisions might have to be made based upon interim analysis results and how this will affect an ongoing study.

OVERLOOKED OR INADEQUATELY DESCRIBED AREAS

Matching in case-control studies.

A weakness that often surfaces in sessions reviewing research proposals is an inadequate description of matching. Matching is commonly used in case-control studies by selecting for each case a control with the same value of the confounding variable. However, in our experience, the term “matching” is used too loosely. To a reviewer matching implies the recruitment of matched pairs. This may not be the intention of the investigators or the planned statistical analysis approach. A proposal that states that the participants will be matched according the gender, race/ethnicity, age, and body mass index would raise quite a few questions because ‘matching’ on all these variables would be quite difficult to achieve in practice. Often what the investigator really would like to insure is that the study groups will be balanced with respect to these characteristics. This is described as “frequency matching”. For continuous variables, such as age, the range that is considered a “match” needs to be specified. Indicate the target age range that is clinically comparable for your study, e.g., within 2 years or 5 years. Avoid matching on variables that are not known confounders as this may lead to loss of power. 20

Missing data prevention

It is well known that dropouts and certain missing data patterns can impact a study’s validity. Since statistical analyses cannot cure all problems associated with missing data, prevention is the best policy. To minimize dropouts and missed study visits, verify that the proposal has included a retention plan. Incorporate study procedures that may help to reduce the amount missing data, such as making regular calls to participants to better maintain contact as the study is underway. Every member of the research team must appreciate the need to reschedule or repeat key study visits or labs to the extent possible if the primary outcome measurement was not obtained. In order to obtain an analysis set that is consistent with the intention-to-treat principle, continue to schedule follow-up visits and collect primary outcome measurements for subjects who have discontinued their assigned treatment.

The integrity of the statistical analysis depends on the quality of the data. Obviously a study must contain high quality data (garbage in, garbage out), but steps to ensure this are frequently overlooked. Describe in the research proposal how data will be collected, de-identified, stored, and protected. It is vital that the clinical research team becomes skilled at data management. Meet with a database expert early to discuss the design of a database and related forms and involve the statistician in the review of the forms. Development of the proper data forms and database prior to study activation is essential.

We have presented guidance to be considered when developing the statistical plan in proposals for clinical and translational research. All these approaches have the common theme of eliminating or reducing bias and improving study quality. Planning the statistical methodology IN ADVANCE is crucial for maintaining the integrity of clinical research. We hope we have conveyed that developing the statistical methods for a research proposal is a collaborative effort between statistical and clinical research professionals.

Writing the statistical plan is a multidisciplinary effort. Both the clinical investigator and statistician on the research team need to carefully review the final product and ensure that the science and statistics correspond correctly. Just as a statistician who can understand the clinical aspect of the research is particularly advantageous, endeavor to learn all you can from the statistical expert. Ask the statistician to explain the rationale of the statistical methodology so you can defend the statistical plans without the statistician at your side. The clinical investigator may not have to know how to perform complex analyses but does need to understand the general statistical reasoning behind the proposed statistical design and analysis. When clinical investigators have a basic proficiency in statistical methodology, not only are collaborations with statisticians more dynamic and fruitful, but the potential to develop into a strong, independent clinical investigator and mentor increases. This leads to the design and execution of more efficient and advanced research, increasing the productivity of the entire research team.

Statistical Resources and Education

What if the researcher does not have funding to support a biostatistician? One option is to include a biostatistician as a co-investigator in your grant proposal to cover salary and supplies needed to implement the statistical methods described in the grant. Hopefully there is a department or division of Biostatistics or related field at your or a nearby institution. If not, long distance collaborations can succeed via conference calls and email. The American Statistical Association (ASA) has an ASA consulting section < http://www.amstat.org/sections/cnsl/ > where a clinical investigator can get assistance in finding a statistical consultant.

Some useful statistical websites for general statistical information and definitions include “The Little Handbook of Statistical Practice” < http://www.tufts.edu/~gdallal/LHSP.HTM >; “HyperStat Online Statistics Textbook” < http://davidmlane.com/hyperstat/index.html >; WISE Web Interface for Statistical Education < http://wise.cgu.edu/index.html >. Clinical trial statistical guidelines are documented in the International Conference on Harmonisation (ICH) Guidance for industry: E9 Statistical principles for clinical trials < http://www.fda.gov/ >. 11

As of September 2009, 46 medical research institutions in the United States have been granted a Clinical and Translational Science Award (CTSA, < www.ncrr.nih.gov/crctsa >). When the CTSA program is fully implemented, it will support approximately 60 centers across the nation. Some CTSA awardees offer biostatistical collaboration or institutional pilot grants for early career clinical investigators in need of statistical expertise. Many of these research centers offer Biostatistics courses or seminar series that are specifically designed for clinical researchers. This paper evolved from a CTSA course, “Clinical Research from Proposal to Implementation”, taught at the University of Texas Southwestern at Dallas. Take advantage of any such course offerings and resources.

A successful research proposal requires solid statistical methodology. The written statistical methods section is the result of teamwork between the clinical investigators and statisticians. Collaborating with a statistician early and often will help the study proposal evolve into a strong application that increases opportunities for scientific acceptance and funding for conducting important clinical research studies.

Acknowledgments

Grant support: NIH CTSA grant UL1 RR024982

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An research proposal examples on statistics is a prosaic composition of a small volume and free composition, expressing individual impressions and thoughts on a specific occasion or issue and obviously not claiming a definitive or exhaustive interpretation of the subject.

Some signs of statistics research proposal:

• the presence of a specific topic or question. A work devoted to the analysis of a wide range of problems in biology, by definition, cannot be performed in the genre of statistics research proposal topic.
• The research proposal expresses individual impressions and thoughts on a specific occasion or issue, in this case, on statistics and does not knowingly pretend to a definitive or exhaustive interpretation of the subject.
• As a rule, an essay suggests a new, subjectively colored word about something, such a work may have a philosophical, historical, biographical, journalistic, literary, critical, popular scientific or purely fiction character.
• in the content of an research proposal samples on statistics , first of all, the author’s personality is assessed - his worldview, thoughts and feelings.

The goal of an research proposal in statistics is to develop such skills as independent creative thinking and writing out your own thoughts.

Writing an research proposal is extremely useful, because it allows the author to learn to clearly and correctly formulate thoughts, structure information, use basic concepts, highlight causal relationships, illustrate experience with relevant examples, and substantiate his conclusions.

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RESEARCH PROPOSAL ON STATISTICAL ANALYSIS ON FACTORS AFFECTING ACADEMIC ACHEIVMENT OF FEMALE STUDENTS IN AMBO UNIVERSTIY (IN THE CASE OF COLLEGE NATURAL AND COMPUTATIONAL SCIENCE).

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What does friendship look like in America?  

Americans place a lot of importance on friendship. In fact, 61% of U.S. adults say having close friends is extremely or very important for people to live a fulfilling life, according to a recent Pew Research Center survey . This is far higher than the shares who say the same about being married (23%), having children (26%) or having a lot of money (24%).

Pew Research Center conducted this analysis to understand Americans’ views of and experiences with friendship. It is based on a survey of 5,057 U.S. adults conducted from July 17-23, 2023. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories.  Read more about the ATP’s methodology .

Here are the  questions used for the analysis , along with responses, and its methodology .

We decided to ask a few more questions to better understand how Americans are experiencing friendship today. Here’s what we found:  

Number of close friends

A narrow majority of adults (53%) say they have between one and four close friends, while a significant share (38%) say they have five or more. Some 8% say they have no close friends.

There’s an age divide in the number of close friends people have. About half of adults 65 and older (49%) say they have five or more close friends, compared with 40% of those 50 to 64, 34% of those 30 to 49 and 32% of those younger than 30. In turn, adults under 50 are more likely than their older counterparts to say they have between one and four close friends.

There are only modest differences in the number of close friendships men and women have. Half of men and 55% of women say they have between one and four close friends. And 40% of men and 36% of women say they have five or more close friends.

Gender of friends

Most adults (66%) say all or most of their close friends are the same gender as them. Women are more likely to say this than men (71% vs. 61%).

Among adults ages 50 and older, 74% of women – compared with 59% of men – say all or most of their close friends are the same gender as them. Among adults younger than 50, the difference is much smaller: 67% of women in this age group say this, as do 63% of men.

Race and ethnicity of friends

A majority of adults (63%) say all or most of their close friends are the same race or ethnicity as them – though this varies across racial and ethnic groups.

White adults (70%) are more likely than Black (62%), Hispanic (47%) and Asian adults (52%) to say this.

This also differs by age. Adults 65 and older are the most likely (70%) to say all or most of their close friends share their race or ethnicity, compared with 53% of adults under 30 – the lowest share among any age group.

Satisfaction with friendships

The majority of Americans with at least one close friend (72%) say they are either completely or very satisfied with the quality of their friendships. Those 50 and older are more likely than their younger counterparts to be highly satisfied with their friendships (77% vs. 67%).

The survey also finds that having more friends is linked to being more satisfied with those friendships. Some 81% of those with five or more close friends say they are completely or very satisfied with their friendships. By comparison, 65% of those with one to four close friends say the same.

The survey didn’t ask adults who reported having no close friends about their level of satisfaction with their friendships.

What do friends talk about?

Of the conversation topics asked about, the most common are work and family life. Among those with at least one close friend, 58% say work comes up in conversation extremely often or often, while 57% say family comes up this often. About half say the same about current events (48%).

There are differences by gender and age in the subjects that Americans discuss with their close friends:

Differences by gender

Women are much more likely than men to say they talk to their close friends about their family extremely often or often (67% vs. 47%).

Women also report talking about their physical health (41% vs. 31%) and mental health (31% vs. 15%) more often than men do with close friends. The gender gap on mental health is particularly wide among adults younger than 50: 43% of women in this age group, compared with 20% of men, say they often discuss this topic with close friends.

By smaller but still significant margins, women are also more likely than men to talk often about their work (61% vs. 54%) and pop culture (37% vs. 32%) with their close friends.

Men, in turn, are more likely than women to say they talk with their close friends about sports (37% vs. 13%) and current events (53% vs. 44%).

Differences by age

Those ages 65 and older (45%) are more likely than younger Americans to say they often talk with their close friends about their physical health.

There are two topics where young adults – those under 30 – stand out from other age groups.

About half of these young adults (52%) say they often talk with their friends about pop culture. This compares with about a third or fewer among older age groups. And young adults are more likely to say they often talk about their mental health with close friends: 37% say this, compared with 29% of those 30 to 49 and 14% of those 50 and older.

Note: Here are the  questions used for the analysis , along with responses, and its methodology .

• Family & Relationships
• Friendships

Isabel Goddard is a research associate focusing on social trends at Pew Research Center

Few East Asian adults believe women have an obligation to society to have children

Among parents with young adult children, some dads feel less connected to their kids than moms do, how teens and parents approach screen time, most east asian adults say men and women should share financial and caregiving duties, among young adults without children, men are more likely than women to say they want to be parents someday, most popular.

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